Authors:
Yasuyo Kita
and
Nobuyuki Kita
Affiliation:
Intelligent Systems Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba and Japan
Keyword(s):
Geodesic Distance, Virtual Flattening, Clothes Handling, Recognition of Deformable Objects, Robot Vision.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Pattern Recognition
;
Robotics
;
Shape Representation and Matching
;
Software Engineering
Abstract:
We propose a method of virtually flattening a largely deformed surface using three-dimensional images taken from different directions. In a previous paper (Kita and Kita, 2016), we proposed a method of virtually fattening a surface from a 3D depth image according to the calculation of geodesic lines, which are the shortest paths between two points on an arbitrary curved surface. Although the work showed the promise of the proposed approach, only gently curved surfaces can be flattened owing to the limit of the observation being made from one direction. To apply the method to a wider range of surfaces, including sharply curved surfaces, we extended the method to three-dimensional depth images taken from different directions integratively. This was done by combining equations obtained from each observation through the surface points observed commonly in different observations and by solving all the equations simultaneously. Experiments using actual clothing items demonstrated the effec
t of the integration.
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